Technical Field
The present invention relates generally to information processing and, in particular, to individual and user group attributes discovery and comparison from social media visual content.
Description of the Related Art
There is a need to obtain rich and composite consumer attributes from social media. Such social media are becoming increasingly visual with a deluge of content shared by users every day, yet social media listening/analytics are still neglecting shared images and videos.
Traditional social listening tools to derive user attributes are based on the following: (1) text analytics, both in content and stylistic choices (for example to derive psycholinguistic traits); and (2) social connections (friends, followers, following).
Visual Analytics applied to social media content has been limited to the following: (1) sentiment analysis in pictures; (2) group affiliation recognition based on pictures analysis; (3) duplicate detection for image tracking; and (4) general event discovery.
A need remains for a system that derives user attributes from semantic analysis of visual content shared on social media.